Nanoporous Carbon Immunosensor for Highly Accurate and Sensitive Clinical Detection of Glial Fibrillary Acidic Protein in Traumatic Brain Injury, Stroke, and Spinal Cord Injury

胶质纤维酸性蛋白 创伤性脑损伤 脊髓损伤 冲程(发动机) 医学 脊髓 生物医学工程 病理 机械工程 免疫组织化学 精神科 工程类
作者
Sultan Khetani,Razieh Salahandish,Jason Tabor,Matthew J. Chilvers,Sean P. Dukelow,Chester Ho,Christina Campbell,Arindom Sen,Chantel T. Debert,Amir Sanati‐Nezhad
出处
期刊:ACS Biomaterials Science & Engineering [American Chemical Society]
卷期号:9 (6): 3556-3569
标识
DOI:10.1021/acsbiomaterials.3c00048
摘要

Elevated glial fibrillary acidic protein (GFAP) in the blood serum is one of the promising bodily fluid markers for the diagnosis of central nervous system (CNS) injuries, including traumatic brain injury (TBI), stroke, and spinal cord injury (SCI). However, accurate and point-of-care (POC) quantification of GFAP in clinical blood samples has been challenging and yet to be clinically validated against gold-standard assays and outcome practices. This work engineered and characterized a novel nanoporous carbon screen-printed electrode with significantly increased surface area and conductivity, as well as preserved stability and anti-fouling properties. This nano-decorated electrode was immobilized with the target GFAP antibody to create an ultrasensitive GFAP immunosensor and quantify GFAP levels in spiked samples and the serum of CNS injury patients. The immunosensor presented a dynamic detection range of 100 fg/mL to 10 ng/mL, a limit of detection of 86.6 fg/mL, and a sensitivity of 20.3 Ω mL/pg mm2 for detecting GFAP in the serum. Its clinical utility was demonstrated by the consistent and selective quantification of GFAP comparable to the ultrasensitive single-molecule array technology in 107 serum samples collected from TBI, stroke, and SCI patients. Comparing the diagnostic and prognostic performance of the immunosensor with the existing clinical paradigms confirms the immunosensor's accuracy as a potential complement to the existing imaging diagnostic modalities and presents a potential for rapid, accurate, cost-effective, and near real-time POC diagnosis and prognosis of CNS injuries.
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